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2006
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Modular Neural Network Task Decomposition Via Entropic Clustering

10 years 5 months ago
Modular Neural Network Task Decomposition Via Entropic Clustering
The use of monolithic neural networks (such as a multilayer perceptron) has some drawbacks: e.g. slow learning, weight coupling, the black box effect. These can be alleviated by the use of a modular neural network. The creation of a MNN has three steps: task decomposition, module creation and decision integration. In this paper we propose the use of an entropic clustering algorithm as a way of performing task decomposition. We present experiments on several real world classification problems that show the performance of this approach.
Jorge M. Santos, Luís A. Alexandre, Joaquim
Added 12 Jun 2010
Updated 12 Jun 2010
Type Conference
Year 2006
Where ISDA
Authors Jorge M. Santos, Luís A. Alexandre, Joaquim Marques de Sá
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